Any organization or technical measure to support the detection of inaccuracies or timely rectification (or deletion) of data supports the principle of accuracy. To understand when accuracy is particularly important and stronger measures are required, an analysis is necessary, on how inaccuracies relate to the fitness for purpose and how they can adversely affect data subjects.
Examples of possible measures in support of accuracy include:
- an organizational measure at design time is the analysis of the minimal level of accuracy required to be fit for purpose;
- an organizational measure at design time is the analysis of the possible adverse impacts that inaccurate data can have on data subjects;
- a design-time measure is the analysis of the accuracy of data obtained from sources other than the data subjects themselves;
- another one is the analysis of whether certain data elements require up-front verification (see Description);
- another design-time measure is to formulate requirements for the support of the rights to information (Art. 13 or 14 GDPR), the right to access (Art. 15 GDPR), and most importantly, the right to rectification (Art. 16 GDPR;
- the same goes for the implementation of notifications of recipients (Art. 19 GDPR) about inaccuracy and rectification;
- at the time of operating the processing activity, the designation of staff to possible manual intervention necessary for verifying accuracy or effectuating rectification is a possible organizational measure;
- the same goes for preparing the Data Protection Officer to effectively deal with rectification requests.